Sebuah Service Untuk Menangani Image Request dalam bentuk Object Plat Nomor

Textify an Image to PDF Converter that uses OCR, and OpenAI LLM for Text Extraction and Formatting.

An AI-powered, but model-agnostic (Optical-Character-Recognition) OCR tool (frontend)

An AI-powered, but model-agnostic (Optical-Character-Recognition) OCR tool

A comprehensive system for detecting and recognizing license plates in real-time, combining image processing, object detection, and optical character recognition (OCR) to provide an accurate and efficient solution for automatic license plate recognition, with also double GUI, both for the Security Manager and for the Car User.

DocumentAI-std is a Python library designed to facilitate and standardize document analysis and processing tasks. It offers functionality for handling document elements, performing optical character recognition (OCR), and managing document datasets.

Machine Learning APIs for common use cases, include: General OCR (Simplified/Traditional Chinese), Custom OCR, Image Similarity, Object Recognition, Face Detection, Face Comparison, Human Image Segmentation, Human Attribute Recognition, Pornography Detection, Image Super Resolution, Text Similarity, Car License Plate, etc.

Library to use Google Lens OCR for free, via API used in Chromium on python.

Simple , Scalable and Ready to use ANPR package for Automatic Number Plate Recognition

[ECCV2024] PosFormer: Recognizing Complex Handwritten Mathematical Expression with Position Forest Transformer

Image to text conversion.

**OpenCV Image Processing Toolkit** is a Python-based image processing tool that integrates OpenCV with real-time code reloading. The application features a Tkinter-based GUI that enables users to load images, apply a variety of OpenCV image processing techniques, and view updates instantly.

An automatic election vote counting system using OCR and Object Detection technology on C1 form images.

This project develops an automatic vote counting system for C1 forms using deep learning techniques.

This project is a versatile Optical Character Recognition (OCR) and translation tool designed to process both images and PDF documents and leveraging NLP to translate the text into different languages and give users an option to summarize the contents of a document in their prefered language

script that uses easyocr for scanning .jpg files and renaming them based on read values

This system utilizes Optical Character Recognition (OCR) extracts text, while computer vision techniques map document layout. Then, SIFT (Scale-Invariant Feature Transform) cleverly matches documents to pre-defined templates, even with variations. This intelligent matching helps identify potential fraud for further investigation.